Using Pharmacogenomics to Aid Antidepressant Prescribing

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Using Pharmacogenomics to Aid Antidepressant Prescribing
Using Pharmacogenomics to Aid Antidepressant Prescribing

Major depressive disorder (MDD) is a prevalent condition that affects 10% to 15% of patients during their lifetime1,2 and has significant physical, social, and economic consequences.3,4 The primary goal for treatment of MDD is to treat the underlying symptoms, restore functioning and prevent recurrence of depressive episodes.

Treatment options for MDD include pharmacotherapy, psychotherapy, and somatic therapies (e.g. electroconvulsive therapy, repetitive transcranial magnetic stimulation [rTMS]).5  Despite the number of antidepressants available, 30% to 50% of patients do not respond to the first antidepressant medication, and only 30% of patients achieve remission of symptoms.6-8

In the last decade, scientific advancements in pharmacogenomics or “personalized medicine” have provided alternative methods for matching drugs to individual patients based on their genetic profile. Pharmacogenomics has been successfully used to optimize selection of medications and dosing, and avoid adverse effects.9,10

Several genes and alleles have been identified that may play a role in the response to antidepressants.11 Genetic variants of the serotonin transporter gene (5-HTTLPR, rs4795541) have been shown to determine varying response to selective serotonin reuptake inhibitors (SSRIs).9,12

Based on the presence of either a long (l) or short (s) allele, the patient may have improved or worse response to SSRIs, respectively, owing to twice the expression of the serotonin transporter among those with the long (l) allele.  It has been estimated that 50% to 60% of whites and 25% to 40% of Asians are carriers of the l allele.9,13,14

Catechol-o-methyltransferase (COMT) variants were also shown to be associated with duloxetine response in MDD as measured by the 17-item Hamilton Rating Scale for Depression (HAM-D-17).15 

Aside from drug response, disease remission is an area of significant interest due to its importance in preventing relapses and recurrences of MDD. In a meta-analysis of 33 candidate gene association studies (CGASs) between 5-HTTLPR and antidepressant response, those with l allele had a 28% increased odds of achieving disease remission with SSRIs than those with s allele.12

In another CGAS, calcium/calmodulin-dependent protein kinases (CaMK) single nucleotide polymorphisms (SNPs) were significantly associated with remission from depression among Chinese patients.16 The CaMK pathway appears to be important for neuroplasticity which in turn has been theorized to be one mechanism of antidepressants.17,18

Ethnicity seems to be a modifying factor since response and remission to antidepressants have been shown to differ in certain ethnic groups. For example, Asians who were homozygotes carriers for SLC6A4 STin2 l allele had a four-fold greater response to SSRIs than s carriers.19

Additional polymorphisms were identified to be associated with antidepressant efficacy, most notably brain-derived neurotrophic factor (BDNF), serotonin transporter (SLC6SA4, STin2), serotonin receptors (HTR1A, HTR2A, HTR5), and tryptophan hydroxylase.19 It appears that multiple genes/alleles are involved in determining response to antidepressants, some which may not have been discovered.

Detecting Potential Adverse Effects

Pharmacogenomics may be useful in not only selecting a particular antidepressant for a patient but also in detecting potential adverse effects and reducing premature discontinuations of antidepressants.

It is estimated that 30% of patients discontinue antidepressants within the first six weeks of starting antidepressant treatment.20 When evaluating adverse effects of antidepressants, both pharmacokinetic (‘how the body affects the drug') and pharmacodynamic (‘how the drug affects the body') factors must be considered.21

Pharmacokinetically, most antidepressants undergo metabolism by the cytochrome P450 (CYP) system, most notably the CYP2C19 and CYP2D6 enzymes.22  These enzymes have many polymorphisms which can affect the degree of drug metabolism and side effects.10 For example, variants of the CYP2D6 enzyme can predispose individuals to being either ultra-rapid metabolizers (UMs), extensive metabolizers (EMs), intermediate metabolizers (IMs), or poor metabolizers (PMs) of drugs that undergo metabolism by CYP2D6.23-25

In one study, patients identified as PMs who received medications influenced by CYP2D6 isoenzyme had significantly more moderate or marked side effects compared to individuals identified as UMs.26  In addition, patients who were PMs of CYP2D6 had significantly longer hospitalization stays due to greater side effect burden from antidepressants than patients with other metabolizer status.27

In a recent Genome-Based Therapeutic Drugs for Depression (GENDEP) study report, while CYP2C19 and CYP2D6 genotype variants predicted serum concentrations of escitalopram and nortriptyline and their metabolites, neither genotype nor serum concentrations predicted treatment response.28

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